Evolutionary algorithms outperform traditional methods in solving complex control problems.
The article investigates different optimization algorithms for solving complex control problems using neural networks. By applying various mathematical methods, the researchers reduced the original problem to a simpler form and used neural networks to approximate the solutions. They tested different optimization algorithms and found that evolutionary algorithms like the genetic algorithm performed better in terms of speed and accuracy compared to traditional methods.
